Elastic Confluence connector reference | Enterprise Search documentation [8.9]

IMPORTANT: No additional bug fixes or documentation updates will be released for this version. For the latest information, see the current release documentation.

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Elastic Confluence connector referenceedit

The Elastic Confluence connector is a connector for Atlassian Confluence.

Availability and prerequisitesedit

This connector is available as a connector client using the Python connectors framework. This connector client is compatible with Elastic versions 8.7.0+. To use this connector, satisfy all connector client requirements.

This connector is in beta and is subject to change. The design and code is less mature than official GA features and is being provided as-is with no warranties. Beta features are not subject to the support SLA of official GA features.

Usageedit

To use this connector as a native connector, see Native connectors (managed service).

To use this connector as a connector client, see Connector clients.

For additional operations, see Using connectors.

Compatibilityedit

Confluence Cloud or Confluence Server versions 7 or later.
Confluence Data Center editions are not currently supported.

Configurationedit

When using the connector client workflow, initially these fields will use the default configuration set in the connector source code. These are set in the get_default_configuration function definition.

These configurable fields will be rendered with their respective labels in the Kibana UI. Once connected, you’ll be able to update these values in Kibana.

The following configuration fields are required to set up the connector:

data_source

Dropdown to determine the Confluence platform type: Confluence Cloud or Confluence Server. Default value is Confluence Server.

username

The username of the account for Confluence server.

password

The password of the account to be used for the Confluence server.

account_email

The account email for the Confluence cloud.

api_token

The API Token to authenticate with Confluence cloud.

confluence_url

The domain where the Confluence is hosted. Examples:

https://192.158.1.38:8080/
https://test_user.atlassian.net/

spaces

Comma-separated list of Space Keys to fetch data from Confluence server or cloud. If the value is *, the connector will fetch data from all spaces present in the configured spaces. Default value is *. Examples:

EC, TP
*

ssl_enabled

Whether SSL verification will be enabled. Default value is False.

ssl_ca

Content of SSL certificate. Note: If ssl_enabled is False, the value in this field is ignored. Example certificate:

-----BEGIN CERTIFICATE-----
MIID+jCCAuKgAwIBAgIGAJJMzlxLMA0GCSqGSIb3DQEBCwUAMHoxCzAJBgNVBAYT
...
7RhLQyWn2u00L7/9Omw=
-----END CERTIFICATE-----

retry_count

The number of retry attempts after failed request to Confluence. Default value is 3.

concurrent_downloads

The number of concurrent downloads for fetching the attachment content. This speeds up the content extraction of attachments. Defaults to 50.

Deployment using Dockeredit

You can deploy the Confluence connector as a self-managed connector client using Docker. Follow these instructions.

Step 1: Download sample configuration file

Download the sample configuration file. You can either download it manually or run the following command:

curl https://raw.githubusercontent.com/elastic/connectors/main/config.yml.example --output ~/connectors-python-config/config.yml

Remember to update the --output argument value if your directory name is different, or you want to use a different config file name.

Step 2: Update the configuration file for your self-managed connector

Update the configuration file with the following settings to match your environment:

elasticsearch.host
elasticsearch.password
connector_id
service_type

Use confluence as the service_type value. Don’t forget to uncomment "confluence" in the sources section of the yaml file.

If you’re running the connector service against a Dockerized version of Elasticsearch and Kibana, your config file will look like this:

elasticsearch:
  host: http://host.docker.internal:9200
  username: elastic
  password: <YOUR_PASSWORD>

connector_id: <CONNECTOR_ID_FROM_KIBANA>
service_type: confluence

sources:
  # UNCOMMENT "confluence" below to enable the Confluence connector

  #mongodb: connectors.sources.mongo:MongoDataSource
  #s3: connectors.sources.s3:S3DataSource
  #dir: connectors.sources.directory:DirectoryDataSource
  #mysql: connectors.sources.mysql:MySqlDataSource
  #network_drive: connectors.sources.network_drive:NASDataSource
  #google_cloud_storage: connectors.sources.google_cloud_storage:GoogleCloudStorageDataSource
  #azure_blob_storage: connectors.sources.azure_blob_storage:AzureBlobStorageDataSource
  #postgresql: connectors.sources.postgresql:PostgreSQLDataSource
  #oracle: connectors.sources.oracle:OracleDataSource
  #mssql: connectors.sources.mssql:MSSQLDataSource

Note that the config file you downloaded might contain more entries, so you will need to manually copy/change the settings that apply to you. Normally you’ll only need to update elasticsearch.host, elasticsearch.password, connector_id and service_type to run the connector service.

Step 3: Run the Docker image

Run the Docker image with the Connector Service using the following command:

docker run \
-v ~/connectors-python-config:/config \
--network "elastic" \
--tty \
--rm \
docker.elastic.co/enterprise-search/elastic-connectors:8.9.2.0-SNAPSHOT \
/app/bin/elastic-ingest \
-c /config/config.yml

Refer to this guide in the Python framework repository for more details.

Documents and syncsedit

The connector syncs the following Confluence object types:

Pages
Spaces
Blog Posts
Attachments

Content of files bigger than 10 MB won’t be extracted.
Permissions are not synced. All documents indexed to an Elastic deployment will be visible to all users with access to that Elastic Deployment.

Sync rulesedit

Basic sync rules are identical for all connectors and are available by default.

This connector supports advanced sync rules for remote filtering. These rules cover complex query-and-filter scenarios that cannot be expressed with <basic sync rules. Advanced sync rules are defined through a source-specific DSL JSON snippet.

Advanced sync rules examplesedit

Example 1: Query for indexing data that is in a particular Space with key DEV.

[
  {
    "query": "space = DEV"
  }
]

Example 2: Queries for indexing data based on created and lastmodified time.

[
  {
    "query": "created >= now('-5w')"
  },
  {
    "query": "lastmodified < startOfYear()"
  }
]

Example 3: Query for indexing only given types in a Space with key SD.

[
  {
    "query": "type in ('page', 'attachment') AND space.key = 'SD'"
  }
]

Syncing recently created/updated items in Confluence may be delayed when using advanced sync rules, because the search endpoint used for CQL queries returns stale results in the response. For more details refer to the following issue in the Confluence documentation.

Content Extractionedit

See Content extraction.

Connector client operationsedit

End-to-end testingedit

The connector framework enables operators to run functional tests against a real data source. Refer to Connector testing for more details.

To perform E2E testing for the Confluence connector, run the following command:

$ make ftest NAME=confluence

For faster tests, add the DATA_SIZE=small flag:

make ftest NAME=confluence DATA_SIZE=small

Known issuesedit

There are currently no known issues for this connector. Refer to Known issues for a list of known issues for all connectors.

Troubleshootingedit

See Troubleshooting.

Securityedit

See Security.

Framework and sourceedit

This connector is included in the Python connectors framework.

View the source code for this connector (branch 8.9, compatible with Elastic 8.9).

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